This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Visual interpretation of large amounts of electroencephalogram (EEG) time series data presents several challenges to neurophysiologists, including limited viewing area, array distribution of time series are not correlated with scalp positions, difficulty identifying slight phase shifts between different regions of the scalp. Three-dimensional spatiotemporal isosurface visualizations help resolve many of these challenges by providing in a single image a method for analyzing and interpreting large amounts of EEG data quickly and more interactively than two-dimensional time series visualizations. Secondly, the correlation dimension of EEG is gaining use, but its adoption as a clinical diagnostic tool is limited by the computational demands of the most commonly used algorithms. Finding a way to leverage the computational resources of the TeraGrid might provide great benefit for clinical and research neurophysiologists who may be looking for new ways to extend their toolsets.